Free Statistics

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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 06 Dec 2010 13:48:44 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/06/t1291643322rg5j842b9tlyi0d.htm/, Retrieved Mon, 29 Apr 2024 06:38:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105601, Retrieved Mon, 29 Apr 2024 06:38:46 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact95
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [opgave 8 oef 3] [2010-12-06 13:48:44] [2d936dc014887261753404b7df36ea79] [Current]
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Dataseries X:
7,24
7,52
7,57
7,59
7,58
7,55
7,52
7,55
7,62
7,64
7,68
7,69
7,7
7,6
7,51
7,66
7,69
7,66
7,7
7,72
7,74
7,76
7,72
7,73
7,75
8,1
8,22
8,32
8,07
8,18
8,33
8,34
8,25
8,36
8,36
8,34
8,41
8,39
8,43
8,44
8,49
8,47
8,53
8,52
8,51
8,53
8,54
8,53
8,47
8,63
8,67
8,73
8,57
8,55
8,63
8,65
8,44
8,62
8,37
8,59
8,84
8,72
8,8
8,69
8,68
8,57
8,85
8,85
8,85
8,93
8,75
8,78
8,77
9,03
9,01
9,07
8,99
9,02
8,99
8,98
8,94
8,94
8,75
8,86




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105601&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105601&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105601&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
17.56250.1161601558977170.45
27.68250.06916712303609950.25
38.218333333333330.1784699278632540.61
48.48250.05293649711940420.149999999999999
58.576666666666670.1039522034690010.360000000000001
68.775833333333330.09894519450257040.359999999999999
78.945833333333330.1017535644524940.32

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 7.5625 & 0.116160155897717 & 0.45 \tabularnewline
2 & 7.6825 & 0.0691671230360995 & 0.25 \tabularnewline
3 & 8.21833333333333 & 0.178469927863254 & 0.61 \tabularnewline
4 & 8.4825 & 0.0529364971194042 & 0.149999999999999 \tabularnewline
5 & 8.57666666666667 & 0.103952203469001 & 0.360000000000001 \tabularnewline
6 & 8.77583333333333 & 0.0989451945025704 & 0.359999999999999 \tabularnewline
7 & 8.94583333333333 & 0.101753564452494 & 0.32 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105601&T=1

[TABLE]
[ROW][C]Standard Deviation-Mean Plot[/C][/ROW]
[ROW][C]Section[/C][C]Mean[/C][C]Standard Deviation[/C][C]Range[/C][/ROW]
[ROW][C]1[/C][C]7.5625[/C][C]0.116160155897717[/C][C]0.45[/C][/ROW]
[ROW][C]2[/C][C]7.6825[/C][C]0.0691671230360995[/C][C]0.25[/C][/ROW]
[ROW][C]3[/C][C]8.21833333333333[/C][C]0.178469927863254[/C][C]0.61[/C][/ROW]
[ROW][C]4[/C][C]8.4825[/C][C]0.0529364971194042[/C][C]0.149999999999999[/C][/ROW]
[ROW][C]5[/C][C]8.57666666666667[/C][C]0.103952203469001[/C][C]0.360000000000001[/C][/ROW]
[ROW][C]6[/C][C]8.77583333333333[/C][C]0.0989451945025704[/C][C]0.359999999999999[/C][/ROW]
[ROW][C]7[/C][C]8.94583333333333[/C][C]0.101753564452494[/C][C]0.32[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105601&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105601&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
17.56250.1161601558977170.45
27.68250.06916712303609950.25
38.218333333333330.1784699278632540.61
48.48250.05293649711940420.149999999999999
58.576666666666670.1039522034690010.360000000000001
68.775833333333330.09894519450257040.359999999999999
78.945833333333330.1017535644524940.32







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.135662372691077
beta-0.00391888073192453
S.D.0.033629742822707
T-STAT-0.116530202225587
p-value0.911768206219017

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.135662372691077 \tabularnewline
beta & -0.00391888073192453 \tabularnewline
S.D. & 0.033629742822707 \tabularnewline
T-STAT & -0.116530202225587 \tabularnewline
p-value & 0.911768206219017 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105601&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.135662372691077[/C][/ROW]
[ROW][C]beta[/C][C]-0.00391888073192453[/C][/ROW]
[ROW][C]S.D.[/C][C]0.033629742822707[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.116530202225587[/C][/ROW]
[ROW][C]p-value[/C][C]0.911768206219017[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105601&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105601&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.135662372691077
beta-0.00391888073192453
S.D.0.033629742822707
T-STAT-0.116530202225587
p-value0.911768206219017







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.09364450897678
beta-0.114227922445610
S.D.2.67201374778275
T-STAT-0.0427497510222008
p-value0.967555674848875
Lambda1.11422792244561

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.09364450897678 \tabularnewline
beta & -0.114227922445610 \tabularnewline
S.D. & 2.67201374778275 \tabularnewline
T-STAT & -0.0427497510222008 \tabularnewline
p-value & 0.967555674848875 \tabularnewline
Lambda & 1.11422792244561 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105601&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.09364450897678[/C][/ROW]
[ROW][C]beta[/C][C]-0.114227922445610[/C][/ROW]
[ROW][C]S.D.[/C][C]2.67201374778275[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.0427497510222008[/C][/ROW]
[ROW][C]p-value[/C][C]0.967555674848875[/C][/ROW]
[ROW][C]Lambda[/C][C]1.11422792244561[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105601&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105601&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.09364450897678
beta-0.114227922445610
S.D.2.67201374778275
T-STAT-0.0427497510222008
p-value0.967555674848875
Lambda1.11422792244561



Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
(n <- length(x))
(np <- floor(n / par1))
arr <- array(NA,dim=c(par1,np))
j <- 0
k <- 1
for (i in 1:(np*par1))
{
j = j + 1
arr[j,k] <- x[i]
if (j == par1) {
j = 0
k=k+1
}
}
arr
arr.mean <- array(NA,dim=np)
arr.sd <- array(NA,dim=np)
arr.range <- array(NA,dim=np)
for (j in 1:np)
{
arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
}
arr.mean
arr.sd
arr.range
(lm1 <- lm(arr.sd~arr.mean))
(lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
(lm2 <- lm(arr.range~arr.mean))
bitmap(file='test1.png')
plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
dev.off()
bitmap(file='test2.png')
plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Section',header=TRUE)
a<-table.element(a,'Mean',header=TRUE)
a<-table.element(a,'Standard Deviation',header=TRUE)
a<-table.element(a,'Range',header=TRUE)
a<-table.row.end(a)
for (j in 1:np) {
a<-table.row.start(a)
a<-table.element(a,j,header=TRUE)
a<-table.element(a,arr.mean[j])
a<-table.element(a,arr.sd[j] )
a<-table.element(a,arr.range[j] )
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Lambda',header=TRUE)
a<-table.element(a,1-lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')